Term
| Always consider data in ______ and anticipate ________ ________ for the data collected and analyzed. |
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Definition
| context, reasonable values |
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Term
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Definition
| Any characteristic of a person or thing that can be assigned a number or a category. |
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Term
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Definition
| The person or thing that has a number or category assigned to it. |
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Term
| Variables can be _______ or ________ |
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Definition
| categorical (a category designation, like gender) or quantitative (a numerical value, like height) |
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Term
| Categorical variables can be _______ |
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Definition
| Binary; meaning they have only two possible categories. |
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Term
| What is the most fundamental principle of statistics? |
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Definition
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Term
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Definition
| The phenomenon of a variable taking on different values or categories from observational unit to observational unit. |
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Term
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Definition
| Numbers or categories recorded for the observational units in a study. |
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Term
| What should you always recite when deciding observational units? |
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Definition
| We are recording variable from observational unit to observational unit . |
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Term
| Stasticis is the science of _____ |
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Definition
| Data (not mere numbers, until they have a meaning) |
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Term
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Definition
| The visual display that displays the distribution of a categorical variable. |
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Term
| Distribution of a Variable |
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Definition
| The pattern of variation. With a categorical variable, distribution means the variable's possible categories and the proportion of responses in each. |
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Term
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Definition
| A visual display that is useful for displaying the distribution of relatively small datasets of a quanititve variable. |
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Term
| Each dot in a dotplot represents a difference _________ ______. |
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Definition
Observational Unit
Additional Tips:
- Develop the habit of always labeling the axis with the name of the variable
- Dotplots can be cumbersome to create by hand, so you can use technology
- Dotplots pertain to quantitative variables, unlike bar graphs.
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Term
| What is the key word for statistical tendencies? |
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Definition
| tend or something along those lines |
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Term
| What should you (most of the time) put on the vertical axis of a bar graph? |
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Definition
| A proportion or percentage |
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Term
| Always begin to analyze data by ______ |
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Definition
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Term
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Definition
| Observational units in one group being more likely to be in a certain category or to have higher values than those in another group. |
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Term
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Definition
| How spread out (or variable) the values in a dataset are (quantitative): When describing distribution you refer to both the center and spread! |
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Term
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Definition
| A study refers to the entire group of people or objects of interest. |
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Term
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Definition
| A typically small, part of the population from whom or which data are gathered to learn about the population as a whole. |
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Term
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Definition
| A carefully selected sample that has similar characteristics to the population. |
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Term
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Definition
| The number of observational units studied in a sample |
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Term
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Definition
| An actual list of every member of the population that we want to sample from. |
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Term
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Definition
| A tendency to systematically overrepresent certain segments of the population and to underrepresent others. |
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Term
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Definition
| Samples collected in such a way that members of the population decide for themselves whether or not to participate |
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Term
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Definition
| People or things that are most readily accessible |
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Term
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Definition
| A number that describes a population |
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Term
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Definition
| A number that described a sample. |
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Term
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Definition
| Conditions that have arisen that affects the survey but cannot be reported due to that condition |
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Term
| Categorical Variables usually lead to a parameter/statistic _____ while a quantitative variable leads to _______ |
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Definition
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Term
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Definition
| Variable whose effect you want to study |
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Term
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Definition
| The variable you suspect is affected by the other variable and considered the outcome of interest. |
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Term
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Definition
| Variables that are not considered in the study but that may also be related to the response variable. |
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Term
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Definition
| Variables that prevent us from drawing a cause-effect conclusiong between the explanatory and response variables. |
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Term
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Definition
| Researchers passively observe and record information about observational units. Doesn't control for the possible effects of confounding variables: NO CAUSE AND EFFECT. |
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Term
| In order to draw a cause-effect relationship |
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Definition
| Impose the explanatory variable on the subjects in ways that the groups are nearly identical except for the explanatory variable |
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Term
| When suggesting a potential confounding variable |
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Definition
| Clearly link this variable to both the explanatory variable and the response variable. (Note: This is different from generalizing sample to population) |
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